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owl:sameAs
Inference Rule:
b3s
b3sifp
dbprdf-label
facets
http://dbpedia.org/resource/inference/rules/dbpedia#
http://dbpedia.org/resource/inference/rules/opencyc#
http://dbpedia.org/resource/inference/rules/umbel#
http://dbpedia.org/resource/inference/rules/yago#
http://dbpedia.org/schema/property_rules#
http://www.ontologyportal.org/inference/rules/SUMO#
http://www.ontologyportal.org/inference/rules/WordNet#
http://www.w3.org/2002/07/owl#
ldp
oplweb
skos-trans
virtrdf-label
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About:
covid:PMC7148221
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An Entity of Type :
owl:Thing
, within Data Space :
wasabi.inria.fr
associated with source
document(s)
Attributes
Values
Creator
Li, Hui
Castells, Pablo
Martins, Flávio
García-Durán, Alberto
González, Roberto
Niepert, Mathias
Oñoro-Rubio, Daniel
Ferro, Nicola
Jose, Joemon
Magalhães, João
Silva, Mário
Yilmaz, Emine
is
schema:about
of
named entity 'Users'
named entity 'Reviews'
named entity 'stochastic gradient descent'
named entity 'regularization'
named entity 'sentiment analysis'
named entity 'knowledge graph'
named entity 'knowledge graph'
named entity 'training set'
named entity 'word embeddings'
named entity 'SVD'
named entity 'training data'
named entity 'online retailers'
named entity 'knowledge graph'
named entity 'p-value'
named entity 'Kindle Store'
named entity 'data sets'
named entity 'Digital Music'
named entity 'recommendation problem'
named entity 'Amazon'
named entity 'element-wise multiplication'
named entity 'SVD'
named entity 'regressor'
named entity 'graph'
named entity '2-dimensional'
named entity 'large corpora'
named entity 'sentiment analysis'
named entity 'dot product'
named entity 'sentiment analysis'
named entity 'vector representations'
named entity 'SGD'
named entity 'data sets'
named entity 'TransE'
named entity 'online shopping'
named entity 'sentiment analysis'
named entity 'sentiment analysis'
named entity '2-dimensional'
named entity 'unsupervised learning'
named entity 'Semi-supervised'
named entity 'data sets'
named entity 'regularization'
named entity 'data sets'
named entity 'training data'
named entity 'inference'
named entity 'word2vec'
named entity 'data set'
named entity 'data sets'
named entity 'training set'
named entity 'recommender systems'
named entity 'embedding dimension'
named entity 'product reviews'
named entity 'word embeddings'
named entity 'supervised learning'
named entity 'Singular Value Decomposition'
named entity 'data sets'
named entity 'knowledge graph'
named entity 'knowledge graph'
named entity 'vanilla'
named entity 'sentiment analysis'
named entity 'data sets'
named entity 'L2 regularization'
named entity 'recommender systems'
named entity 'L-BFGS'
named entity 'recommender systems'
named entity 'knowledge graph'
named entity 'tokenize'
named entity 'Euclidean distance'
named entity 'product reviews'
named entity 'sentiment analysis'
named entity 'convolutional neural networks'
named entity 'ELMO'
named entity 'data sets'
named entity 'e-commerce'
named entity 'data sets'
named entity 'learning rate'
named entity 'MSE'
named entity 'word embedding'
named entity 'good performance'
named entity 'sampling'
named entity 't-test'
named entity 'written text'
named entity 'knowledge graphs'
named entity 'trade-off'
named entity 'recommender systems'
named entity 'data sets'
named entity 'accounting'
named entity 'bag-of-words'
named entity 'good performance'
named entity 'recommender systems'
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